Hands-on Python for Finance

The practical guide to using data-driven algorithms in Finance

4.05 (65 reviews)
Udemy
platform
English
language
Programming Languages
category
361
students
5.5 hours
content
Mar 2019
last update
$44.99
regular price

What you will learn

General programing skills in Python and working with common Python interfaces

Using Numpy, Pandas and matplotlib to manipulate, analyze and visualize data

Understand the Time value of money applications and project selection

Getting and with working data, time series forecasting methods and linear models

Understand Correlation and portfolio construction

Be comfortable with Monte Carlo Simulation, Value at Risk and Options Valuation

Description

Did you know Python is the one of the best solution to quantitatively analyse your finances by taking an overview of your timeline? This hands-on course helps both developers and quantitative analysts to get started with Python, and guides you through the most important aspects of using Python for quantitative finance.

You will begin with a primer to Python and its various data structures.Then you will dive into third party libraries. You will work with Python libraries and tools designed specifically for analytical and visualization purposes. Then you will get an overview of cash flow across the timeline. You will also learn concepts like Time Series Evaluation, Forecasting, Linear Regression and also look at crucial aspects like Linear Models, Correlation and portfolio construction. Finally, you will compute Value at Risk (VaR) and simulate portfolio values using Monte Carlo Simulation which is a broader class of computational algorithms.

With numerous practical examples through the course, you will develop a full-fledged framework for Monte Carlo, which is a class of computational algorithms and simulation-based derivatives and risk analytics.

About the Author

Matthew Macarty has taught graduate and undergraduate business school students for over 15 years and currently teaches at Bentley University. He has taught courses in statistics, quantitative methods, information systems and database design.

Content

Python Programming Primer

The Course Overview
Installing the Anaconda Platform
Launching the Python Environment
String and Number Objects
Python Lists
Python Dictionaries (Dicts)
Repetition in Python (For Loops)
Branching Logic in Python (If Blocks)
Introduction to Functions in Python

The Python Data Environment

Introduction to NumPy Arrays
NumPy – A Deeper Dive
Pandas – Part I
Pandas – Part II
Introduction to Scipy.stats
Matplotlib – Part I
Matplotlib – Part II

Time Value of Money

Present Value of a Stream of Cash Flows
Future Value of Single and Multiple Cash Flows
Net Present Value of a Project
Internal Rate of Return
Introduction to Amortization
Creating an Amortization Application

Time Series Evaluation and Forecasting

Opening and Reading a .CSV File
Getting and Evaluating Data
Moving Average Forecasting
Forecasting with Single Exponential Smoothing
Creating and Testing a Simple Trading System

Linear Models, Correlation, and Valuation

Valuing Securities with Pricing Models
Finding Correlations Between Securities
Linear Regression
Calculating Beta and Expected Return
Constructing Portfolios Along the Efficient Frontier

Build a Monte Carlo Simulation App

Introduction to Monte Carlo
Monte Carlo Simulation
Using Monte Carlo Technique to Calculate Value at Risk
Putting It All Together – Monte Simulation Application

Screenshots

Hands-on Python for Finance - Screenshot_01Hands-on Python for Finance - Screenshot_02Hands-on Python for Finance - Screenshot_03Hands-on Python for Finance - Screenshot_04

Reviews

Ajay
November 15, 2022
What I love about this course is that he flys through the material so you really get a birds eye view of how python works for some corp finance. It served my purposes well since python has been a mystery to me so far and other courses get stuck in some laborious file opening or string syntax. this guy zips through it and i also play it at 2x the speed so I don't waste time plodding along. However, I have taken C++ programming and I have done an MBA so the concepts are familiar. Others may find his treatment tough to follow so it's not exactly for those with no prior background
Isaiah
August 26, 2022
The instructor actually walks you through the process and introduces tools that helps you understand Python.
Neil
January 2, 2021
This was based on seeing <5% of the course. Basically watched the introduction plus a few basic vids and got asked to rate the course
Sebastian
December 13, 2020
Well explained & useful tools. it gives a first introduction in financial programming. The only things missing are exercises
Pratyush
May 19, 2020
The course content is good but the presenter doesn't explain a few stuff well. It led to the confusion many a time. Overall the course is nice except for a few jargon which could have been removed.
Andre
January 27, 2020
You will understand how to use Python libraries (Pandas, Numpy, matplotlib) for simple finance calculations. This course might not be the best possible one, but it will get you started.
Razafi
September 18, 2019
ouah, very clear but sometimes very fast for some new elements that supposed known (by instructor !) not by me. So thks a lot. Matt
Solohery
July 26, 2019
Good courses even though you need a pre requisite of minimum knowledge in Python. Monte carlo simulation is pretty accuratly explained in a simple manner. However I do not understand the use of Black Scholes stock pricing in it. Should be good to justify it. The exponential mean average pkg name not really easy to remember

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2256784
udemy ID
3/6/2019
course created date
6/9/2021
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